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The Origins and Consequences of Affective Polarization in the United States Shanto Iyengar 1 , Yphtach Lelkes 2 , Matthew Levendusky 3 , Neil Malhotra 4 , and Sean J. Westwood 5 1 Department of Political Science, Stanford University 2 Annenberg School of Communication, University of Pennsylvania 3 Department of Political Science, University of Pennsylvania 4 Graduate School of Business, Stanford University 5 Department of Government, Dartmouth College April 23, 2018 Word count: 7,970 Citation count: 100 America, we are told, is a divided nation. What does this mean? Political elites— particularly members of Congress—increasingly disagree on policy issues (McCarty, Poole, and Rosenthal, 2006), though there is still an active debate about whether the same is true of the mass public (Abramowitz and Saunders, 2008; Fiorina, Abrams, and Pope, 2008). But regardless of how divided Americans may be on the issues, a new type of division has emerged in the mass public in recent years: ordinary Americans increasingly dislike and distrust those from the other party. Democrats and Republicans both say that the other party’s members are hypocritical, selfish, and closed-minded, and they are unwilling to socialize across party lines, or even to partner with opponents in a variety of other activities. This phenomenon of animosity between the parties is known as affective polarization. We trace the origins of affective 1

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Page 1: The Origins and Consequences of A ective Polarization in the …seanjwestwood/papers/ARPS.pdf · 2018-04-23 · Iyengar and Westwood (2015) developed an Implicit Association Test

The Origins and Consequences of Affective Polarizationin the United States

Shanto Iyengar1, Yphtach Lelkes2, Matthew Levendusky3, Neil Malhotra4,and Sean J. Westwood5

1Department of Political Science, Stanford University2Annenberg School of Communication, University of Pennsylvania

3Department of Political Science, University of Pennsylvania4Graduate School of Business, Stanford University5Department of Government, Dartmouth College

April 23, 2018

Word count: 7,970

Citation count: 100

America, we are told, is a divided nation. What does this mean? Political elites—

particularly members of Congress—increasingly disagree on policy issues (McCarty, Poole,

and Rosenthal, 2006), though there is still an active debate about whether the same is true

of the mass public (Abramowitz and Saunders, 2008; Fiorina, Abrams, and Pope, 2008).

But regardless of how divided Americans may be on the issues, a new type of division has

emerged in the mass public in recent years: ordinary Americans increasingly dislike and

distrust those from the other party.

Democrats and Republicans both say that the other party’s members are hypocritical,

selfish, and closed-minded, and they are unwilling to socialize across party lines, or even

to partner with opponents in a variety of other activities. This phenomenon of animosity

between the parties is known as affective polarization. We trace the origins of affective

1

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polarization to the power of partisanship as a social identity, and explain the variety of factors

that intensify partisan animus. We also explore the consequences of affective polarization,

highlighting how partisan affect influences attitudes and behaviors well outside the political

sphere. Finally, we discuss strategies that might mitigate partisan discord, and conclude

with some suggestions for future work.

Affective Polarization: an Outgrowth of Partisan Social

Identity

Homo sapiens is a social species; group affiliation is essential to our sense of self. Indi-

viduals instinctively think of themselves as representing broad socio-economic and cultural

categories rather than as distinctive packages of traits (Brewer, 1991; Tajfel, 1978). Among

these categories, political parties subsist precisely because group identities are so stable and

significant (Lipset and Rokkan, 1967).

In the U.S., partisanship is about identifying with the “Democrat” group or the “Re-

publican” group (Green, Palmquist, and Schickler, 2002; Huddy, Mason, and Aarøe, 2015).

A host of behavioral consequences flow from that identification. When we identify with a

political party, we instinctively divide up the world into an in group (our own party), and

an out group (the opposing party; see Tajfel and Turner 1979). A vast literature in social

psychology demonstrates that any such in-group/out-group distinction, even one based on

the most trivial of shared characteristics, triggers both positive feelings for the in group, and

negative evaluations of the out group (see, e.g., Billig and Tajfel, 1973). The more salient

the group to the sense of personal identity, the stronger these inter-group divisions (Gaertner

et al., 1993).

Partisanship is a particularly salient and powerful identify for several reasons. First, it is

acquired at a young age, and rarely changes over the life-cycle, notwithstanding significant

shifts in personal circumstances (Sears, 1975). Second, political campaigns—the formal

2

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occasions for expressing ones partisan identity—recur frequently, and last for many months

(or even years) in the contemporary U.S. Indeed, some even argue that modern governance is

effectively always about the next campaign (Lee, 2016), meaning that individuals constantly

receive partisan cues from elites. It is no surprise, therefore, that ordinary Americans see

the political world through a partisan prism.

From a social identity perspective, affective polarization is a natural offshoot of this sense

of partisan group identity: “the tendency of people identifying as Republicans or Democrats

to view opposing partisans negatively and copartisans positively” (Iyengar and Westwood,

2015, 691). However, changes in the contemporary political and media environment have

further exacerbated the divide in recent years, as we explain below.

Our conceptualization of polarization as rooted in affect and identity stands in contrast

to a long tradition in political science of studying polarization as the difference between the

policy positions of Democrats and Republicans (Fiorina, Abrams, and Pope, 2005). Indeed,

there is ongoing scholarly disagreement over the extent of such ideological polarization.

Some scholars argue that the mass public has polarized on the issues, citing a decline in

the number of ideological moderates and a near doubling of the average distance between

the ideological self-placement of non-activist Democrats and Republicans between 1972 and

2004 (Abramowitz and Saunders, 2008). Others dispute this description of the masses,

maintaining that the median citizen remains a centrist rather than an extremist on most

issues (Fiorina, Abrams, and Pope, 2008).

We do not take a position on this ongoing debate. Rather, we argue that affective polar-

ization is largely distinct from the ideological divide, and that extremity in issue opinions is

not a necessary condition for affective polarization (Iyengar, Sood, and Lelkes, 2012; Mason,

2015). Indeed, in some settings, affective polarization can increase while ideological divisions

shrink (Levendusky and Malhotra, 2016a). While there are important connections between

affective and ideological polarization that we return to below (Abramowitz and Webster,

2016), they are theoretically and empirically distinct concepts. Here, we focus exclusively

3

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on the affective dimension of polarization.

How Do We Measure Affective Polarization?

Scholars have used three main classes of techniques to measure affective polarization: survey

self-reports of partisan affect, implicit or sub-conscious tests of partisan bias, and behavioral

measures of inter-personal trust and group favoritism or discrimination based on partisan

cues.

Survey Self-Reports

Survey self-reports are the most basic and widely used measure of affective polarization in the

literature. While scholars have relied on a number of different survey items, the most central

is the “feeling thermometer” question from the American National Election Study (ANES)

time series. The feeling thermometer was originally created as a “neutrally worded means

of eliciting responses to a wide variety of candidates” (Weisberg and Rusk, 1970, 1168), but

has become the primary vehicle for measuring affect toward a wide range of groups in the

electorate. Typically respondents are asked to rate “Democrats” and “Republicans” (or the

Democratic and Republican Parties) on a 101-point scale ranging from cold (0) to warm

(100). Affective polarization is then computed as the difference between the score given to

the party of the respondent and the score given to the opposing party. In the ANES time

series (see Figure 1), this measure shows a significant increase in affective polarization in the

period after 1980, rising from 22.64 degrees in 1978 to 40.87 degrees in 2016 (Westwood and

Lelkes, 2018; Iyengar, Sood, and Lelkes, 2012). It is particularly noteworthy that 1) it is not

so much that people like their own party more over time; rather, there is an increase in out-

party animus, especially in recent years and 2) that affective polarization actually decreased

between 2012 and 2016. Other over-time measures of partisan affect—for example, those

from the Pew Research Center—show similar patterns (Pew Research Center, 2017).

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Figure 1: Partisan Feeling and Affective Polarization Overtime (ANES)

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In−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feelingIn−group feeling

Affective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective Polarization

Out−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feeling

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1980 1990 2000 2010

Year

While the feeling thermometer is the workhorse survey item, scholars have also adopted

a variety of alternative measures. For instance, Levendusky (2018) and Levendusky and

Malhotra (2016a) use trait ratings of party supporters to measure affective discord: are they

intelligent, open-minded, and generous, or hypocritical, selfish, and mean (see also Garrett

et al., 2014; Iyengar, Sood, and Lelkes, 2012)? Levendusky and Malhotra (2016a) also use

the number of likes and dislikes of the parties people can bring to mind as a quasi-behavioral

measure. Other scholars have substituted the extent to which the presidential candidates

elicit either positive or negative emotional responses as the metric for assessing affective

polarization (Lelkes, Sood, and Iyengar, 2017).

A more unobtrusive measure of partisan affect is social distance, the extent to which

individuals feel comfortable interacting with out-group members in a variety of different

settings. If partisnaship is an important social identity in its own right, partisans should be

averse to entering into close inter-personal relations with their opponents. Iyengar, Sood,

and Lelkes (2012) show that Americans have become increasingly averse to the prospect

of their child marrying someone from the opposing party. In 1960, only 4-5% were upset

with their child marrying someone from the out party, but that figure had jumped to one-

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third of Democrats and one-half of Republicans by 2010 (416-8). However, Klar, Krupnikov,

and Ryan (Forthcoming) show that social distance measures conflate partisan animus and

a dislike of politics: when people are asked about their child marrying someone from the

opposing party, they assume that partisanship is a salient part of that person’s identity.

When respondents were told prior to the question that the potential spouse in question is

largely apolitical, their opposition falls sharply. Similarly, their opposition rises to same-

party marriage when they are told the person frequently discusses politics. This suggests

that part of the opposition to inter-party marriage (and other types of social distance)

may be that people assume “Republicans” and “Democrats” are the extremists portrayed

in the media (Levendusky and Malhotra, 2016a), rather than their more typical apolitical

brethren. Alternatively, the finding may reflect the well-known association between politics

and disagreement; most people prefer to be in agreeable relationships. Understanding the

precise limitations of social distance measures is an important topic for future research.

Implicit Measures

A major limitation to survey-based indicators of partisan affect is that they are reactive and

susceptible to intentional exaggeration/suppression based on normative pressures. Unlike

race, gender, and other social divides where group-related attitudes and behaviors are sub-

ject to social norms (Maccoby and Maccoby, 1954), there are no corresponding pressures

to temper disapproval of political opponents. If anything, the rhetoric and actions of po-

litical leaders demonstrate that hostility directed at the opposition is acceptable and often

appropriate. Implicit measures are known to be much harder to manipulate than explicit

self-reports; they are therefore more valid and less susceptible to impression management

(Boysen, Vogel, and Madon, 2006).

Iyengar and Westwood (2015) developed an Implicit Association Test (based on the brief

version of the race IAT) to document unconscious partisan bias. Their results showed that

implicit bias is ingrained with approximately 70% of Democrats and Republicans showing a

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bias in favor of their party. Interestingly, implicit bias is less pronounced than explicit bias

as measured through survey questions; 91% of Republicans and 75% of Democrats in the

same study explicitly evaluated their party more favorably.

To place the results from their party IAT in context Iyengar and Westwood also adminis-

tered the race IAT. Relative to implicit racial bias, implicit partisan bias is more widespread.

The difference in the D-score—the operational indicator of implicit bias—across the party

divide was .50, while the corresponding difference in implicit racial bias across the racial

divide was only .18 (see also Theodoridis (2017) for an application of implicit measures to

the study of partisanship). 1

Behavioral Measures

Of course, one can also critique measures of implicit attitudes, especially on the grounds

that they are weak predictors of relevant behaviors. Given the limits of the attitudinal

approach, scholars have turned to behavioral manifestations of partisan animus in both

lab and naturalistic settings. Iyengar and Westwood (2015) and Carlin and Love (2013)

introduce economic games as a platform for documenting the extent to which partisans are

willing to endow or withhold financial rewards from players who either share or do not

share their partisan affiliation. Using both the trust game and the dictator game, this

work measures partisan bias as the difference between financial allocations to co-partisans

and opposing partisans. Results show that co-partisans consistently receive a bonus while

opposing partisans are subject to a financial penalty.

Iyengar and Westwood (2015) further document the extent of affective polarization by

comparing the effects of partisan and racial cues in non-political settings. In one study, they

asked participants to select one of two candidates for a college scholarship. The candidates—

both high school students—had similar academic credentials, but differed in their ethnicity

(White or African American) or partisanship (Democrat or Republican). The results indi-

1Ryan (2017) shows that when explicit political preferences are weak these underlying implicit preferencesdrive political decision-making.

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cated little racial bias; Whites, in fact, preferred the African American applicant (55.8%).

79.2% of Democrats picked the Democratic applicant and 80% of Republicans picked the

Republican applicant. These results held even when the out-partisan candidate had a sig-

nificantly higher GPA (4.0 v. 3.5); the probability of a partisan selecting the more qualified

out-party candidate was never above 30%.

The scholarship study showed that partisan cues exert strong leverage over non-political

attitudes. This phenomenon of affective spillover has been documented in a variety of do-

mains including evaluations of job applicants (Gift and Gift, 2015), dating behavior (Huber

and Malhotra, 2017), and online labor markets (McConnell et al., 2018). This work con-

sistently shows that partisanship has bled into the non-political sphere, driving ordinary

citizens to reward co-partisans and penalize opposing partisans, a point to which we return

below.

Regardless of measurement technique, the literature consistently documents an affective

and behavioral divide between the in-party and the out-party. Further measurement exercises

show that while affective polarization predicts both political and private behavior, it has yet

to rise to the level of overt discrimination as conceptualized in social psychology (Lelkes and

Westwood, 2017). Understanding the limits to affective polarization, and what constrains

these sentiments, therefore, is another important realm for future study.

Origins and Causes of Affective Polarization

A number of features of the contemporary environment have exacerbated partisans’ procliv-

ity to divide the world into a liked in group (one’s own party) and a disliked out group (the

opposing party). First, in the last 50 years, the percentage of “sorted” partisans, i.e., parti-

sans who identify with the party most closely reflecting their ideology, has steadily increased

(Levendusky, 2009). When most Democrats [Republicans] are also liberals [conservatives],

they are less likely to encounter conflicting political ideas and identities (Roccas and Brewer,

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2002), and are more likely see non-identifiers as socially distant. Sorting likely leads people to

perceive both opposing partisans and co-partisans as more extreme than they really are, with

misperceptions being more acute for opposing partisans (Levendusky and Malhotra, 2016b).

As partisan and ideological identities became increasingly aligned, other salient social iden-

tities, including race and religion, also converged with partisanship. White evangelicals,

for instance, are overwhelmingly Republican today, and African-Americans overwhelmingly

identify as Democrats. This decline of cross-cutting identities is at the root of affective

polarization according to Mason (2015, 2018b). She has shown that those with consistent

partisan and ideological identities became more hostile towards the out-party without nec-

essarily changing their ideological positions, and those that have aligned religious, racial,

and partisan identities react more emotionally to information that threatens their partisan

identities or issue stances. In essence, sorting has made it much easier for partisans to make

generalized inferences about the opposing side, even if those inferences are inaccurate.

While reinforcing social identities seem to be a key factor explaining affective polarization,

other work finds that ideological polarization also impacts affective polarization (Rogowski

and Sutherland, 2016; Bougher, 2017). Observational time-series and panel data indicate

that increasing ideological extremity and constraint are both associated with stronger par-

tisan affect (Bougher, 2017), and experimental work that manipulates the degree to which

a candidate is “liberal” or “conservative” also impacts affective polarization (Rogowski and

Sutherland, 2016; Webster and Abramowitz, 2017).

The high-choice media environment and the proliferation of partisan outlets are frequently

blamed for the current polarized environment (e.g., Lelkes, Sood, and Iyengar, 2017). The ar-

gument goes that partisan news activates partisan identities and subsequent feelings towards

the political parties. One feature of any social identity is that, in order to fit in with the

group, identifiers must adopt the attitudes of prototypical in-group members (Hogg, 2001).

Partisan outlets—many of which depict the opposing party in harsh terms, often comparing

out-partisans to Nazis and Communists (Berry and Sobieraj, 2014), and by focusing dis-

9

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proportionately on out-party scandals (real or imagined)—inculcate hostility toward the out

group (Puglisi and Snyder, 2011).

Further, the lack of balanced content in these outlets may persuade viewers to adopt

extreme ideological positions (Levendusky, 2013), which, in turn, increases affective polar-

ization (Rogowski and Sutherland, 2016; Webster and Abramowitz, 2017). While both survey

and experimental research supports this hypothesis (Stroud, 2010; Levendusky, 2013), the

precise mechanism is unclear because the treatment is typically exposure to an outlet or

cable news show, making it difficult to tease apart the effects of exposure to extreme policy

positions, the priming of partisanship, or the cultivation of hostility toward the other side.

It is far from clear, however, that partisan news actually causes affective polarization.

First, those who are the most polarized are, of course, more motivated to watch partisan

news (Arceneaux and Johnson, 2013). Arguably, therefore, partisan news has little impact

on polarization. Levendusky (2013), however, finds that exposure to partisan news makes

those with extreme attitudes even more extreme. While these studies focus on ideological

polarization, the ability to opt out of exposure to partisan news may also further weaken the

impact of partisan media on affective polarization.

Another mitigating factor is that partisans may not have a clear preference for ideologi-

cally or identity-consistent information. While some studies have found evidence of selective

exposure to partisan information (e.g., Stroud, 2011), others find that Americans typically

select ideologically neutral content (e.g., Gentzkow and Shapiro, 2011). So even if partisan

news or other identity-consistent information heightens affective polarization, few people

may actually limit their exposure to sources representing a particular identity or ideology

(see also Bakshy, Messing, and Adamic, 2015).

The relationship between Internet access, a major route to partisan media, and affective

polarization is similarly contested. Using state Right-of-Way laws as an instrument for

Internet access, Lelkes, Sood, and Iyengar (2017) find a positive small, relationship between

Internet access and affective polarization. On the other hand, Boxell, Gentzkow, and Shapiro

10

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(2017) find that affective polarization has increased the most among those least likely to use

social media and the Internet. Given these inconsistent results, it is too early to conclude

that Internet usage (and the availability of a wider array of information) plays a definite role

in the growth of affective polarization.

While the high-choice media environment of cable and the Internet allow those uninter-

ested in politics to “check out,” exposure to partisan news can occur in other ways. First,

as people spend more time online and on social network sites, they are more likely to be

inadvertently exposed to polarizing content by others in their network (Bakshy, Messing,

and Adamic, 2015). Additionally, people may be exposed to partisan news content indi-

rectly through discussion with peers. Druckman, Levendusky, and McLain (2018) randomly

assigned subjects to watch partisan media, and, later participate in discussions with those

who did not watch the stimuli. Those in groups that contained people who watched the

stimuli were significantly more (ideologically) polarized than those who were not in such

groups. This result suggests that partisan media—and other related outlets—may play a

more significant role than initially thought because their messages can be amplified by social

networks and two-step communication flows.

Partisan commentary is not the only type of media content that can polarize Americans.

First, the mainstream media has increasingly focused on polarization. According to one

content analysis, there are roughly 20 percent more stories about polarization in America

today than there were at the turn of the 21st century (Levendusky and Malhotra, 2016a).

Experimental evidence suggests that coverage of polarization increases affective polarization

but decreases ideological polarization (Levendusky and Malhotra, 2016a).

Political campaigns also exacerbate partisan tensions (Sood and Iyengar 2016). Across

recent election cycles, people were between 50 percent and 150 percent more affectively po-

larized by election day than they were a year earlier. Additionally, by identifying people who

live in the designated market area of a neighboring battleground state, Sood and Iyengar

(2016) show that political advertisements, and especially negative advertising, have partic-

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ularly strong effects on affective polarization (see also Iyengar, Sood, and Lelkes, 2012).

Political campaigns may heighten tensions in a number of ways. For instance, campaigns

make partisanship more salient (Michelitch and Utych, Forthcoming), and regularly run ads

that portray the other side as an existential threat.

Finally, increasingly homogeneous online and offline interpersonal networks may be con-

tributing to affective polarization. As partisans become more isolated from each other (Gim-

pel and Hui, 2015) in their real and virtual lives, they are more likely to encounter only

like-minded voices, further exacerbating polarization. While provocative, and certainly part

of the popular discourse, the scholarly evidence on social homophily is mixed. For one thing,

there is little evidence that people are increasingly living in partisan enclaves (Mummolo

and Nall, 2017). However, it is clear that families have become more politically homoge-

neous. Spousal agreement on party affiliation now exceeds 80 percent, with parent-offspring

agreement at 75 percent, both figures representing large increases in family agreement since

the 1960s (Iyengar, Konitzer, and Tedin, 2017). In the case of online behavior, as we noted

earlier, the first analysis of partisan segregation in the audience for online news (Gentzkow

and Shapiro, 2011) showed that most Americans encountered diverse points of view. More

recent work, however, suggests that the polarization of online news audiences has increased,

especially when considering exposure to election-related news. All told, therefore, it is pre-

mature to reach any firm conclusions about the role of “echo chambers,” either in-person or

online, as causes of affective polarization.

The Non-Political Consequences of Affective Polariza-

tion

One major concern is that partisan animus might spill over and affect behaviors and attitudes

outside the political realm. It is one thing if partisan disagreements are confined to political

contestation, but quite another if everyday interactions and life choices are compromised by

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politics.

For instance, does partisanship affect the social relations we seek to enter into, whether

it be friendships, romantic relationships, or marriages? Since partisanship increasingly sig-

nals core values and worldview, it is unsurprising that partisanship is used to screen social

partners. People may also perceive copartisans to be more physically attractive (Nicholson

et al., 2016).2 Longitudinal survey data has shown that people self-report that they are less

comfortable with social relationships with out partisans. According to Iyengar, Sood, and

Lelkes (2012), the percentage of Americans who would be somewhat or very unhappy if their

child married someone of the opposite party has increased by about 35 percentage points

over the last 50 years, with Republicans especially sensitive to cross-party marriage. These

increases are much larger in the United States compared to a similar advanced democracy

(the United Kingdom). And these preferences appear substantively larger than apolitical

benchmarks such as the 17%-20% of people who would not want their child marrying a fan

of an opposing baseball team (Hersh, 2016). Behavioral data from smartphone activity con-

firms that Americans are averse to cross-partisan dialogue within their families, especially

in the wake of the 2016 election (Chen and Rohla, 2017).

Although people may state that they do not want to enter to in relationships with people

of the opposing party, does their behavior match their self-reports? Observational survey

data has long found that marriages are much more politically homogenous than one would

expect by chance (Stoker, 1995). This finding has been validated in large voter files, which

show that 80.5% of married couples share a party identification (Iyengar, Konitzer, and Te-

din, 2017), and that selection rather than convergence over time explains spousal agreement.3

Of course, any data collected after people have married is of limited utility for assessing

whether people prefer to engage in romantic relationships with people of the opposing party.

2However, Huber and Malhotra (2017) run similar experiments to Nicholson et al. (2016) including morecontextual information along the lines of a conjoint design and find no effect of shared partisanship onperceived attractiveness.

3Using the Catalyst subsample, Hersh and Ghitza (2017) find somewhat lower spousal agreement (70%),but even here, it is still significantly higher than chance alone would predict.

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This is because homophily can be induced by various factors unrelated to selection: (1)

post-marriage conversion; (2) the influence of shared environment; (3) structural features

of the available partner pool. As a result, some recent research has attempted to use data

from online dating websites to assess whether political homophily in relationships is due to

selection based on political profiles. Huber and Malhotra (2017) leverage data from an online

dating website where they have access to both the profile characteristics of daters as well

as their messaging behavior. They find that partisan matching increases the likelihood of a

dyad exchanging messages by 9.5%. To put that finding into context, analogous figures for

dating pairs matched by level of education and religion are 10.6% and 50.0%, respectively.

On the one hand, these substantive effects might be smaller than survey data would imply.

On the other hand, partisan sorting seems to be on a par with socio-economic status, long

considered the major basis for the selection of long-term partners. Huber and Malhotra

(2017) corroborate this finding with data from a survey experiment where partisanship is

randomly manipulated in the dating profiles.

The findings of Huber and Malhotra (2017) appear to conflict with other data from public

online dating profiles (Klofstad, McDermott, and Hatemi, 2013). Although these studies do

not have access to the messaging behavior going on behind the scenes, they find that online

daters usually do not advertise their political preferences, which would seem inconsistent

with the idea of people actively selecting on this information. However, dating behavior

may be changing. The dating website eHarmony reported that dating profiles typically did

not report political affiliation prior to the 2016 presidential election (24.6% of women and

16.5% of men). After the 2016 presidential election, these figures increased to 68% and 47%,

respectively (Kiefer, 2017), suggesting that in the wake of the divisive 2016 election, a sea

change may be underway.

If the thought of romantic relationships with an opposing partisan is a bridge too far,

one might ask whether people are more tolerant of the relationship as merely friendship.

Survey data from the Pew Research Center suggest this is unlikely to be the case. About

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64% of Democrats and 55% of Republicans say they have “just a few” or “no” close friends

who are from the other political party (Pew Research Center, 2017). Huber and Malhotra

(2017) also find in their survey experiment that discordant partisanship decreases people’s

likelihood to being friends with someone even if they do not want a romantic relationship.

Chopik and Motyl (2016) find that living in a politically incongruent area made it more

difficult for people to form friendships. Behavioral data seem to confirm that people seek

to hide their partisanship from peers when they are living in a politically discordant loca-

tion. Using data on political donations, Perez-Truglia and Cruces (2017) find that people

signal their conformity via donations to opposite-party peers, perhaps out of fear of social

reprisal. Finally, Facebook data show that the median proportion of friendship groups that

are ideologically discordant is only about 20% (Bakshy, Messing, and Adamic, 2015).

If people seek to socialize with people they are likely to agree with politically, it stands

to reason that they may choose to locate themselves near like-minded individuals. Indeed,

survey data suggests that people self-report desiring to move to locations with fellow parti-

sans (Gimpel and Hui, 2015). The idea of residential sorting based on partisanship was first

popularized by Bishop (2009), who reported descriptive statistics showing that counties had

become more politically homogeneous over time. However, Klinkner (2004) challenged much

of this data analysis by showing that residential sorting has not increased significantly over

the past few decades when one analyzes party registration data instead of presidential vote

returns. Further, in contrast to Gimpel and Hui (2015), Mummolo and Nall (2017) show that

revealed preferences concerning place of residence diverge from stated preferences. Although

people claim they would like to move to a more politically compatible area (e.g., Democrats

claiming they would move to Canada following Bush’s 2004 reelection), mobility data sug-

gests that people are not moving for political reasons, largely because other non-political

factors—such as the quality of the public schools—dominate the decisions of Democrats and

Republicans alike.

Thus far, we have mainly explored if partisanship spills over into people’s social interac-

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tions. But can partisanship also distort economic behavior? Michelitch’s (2015) pioneering

work in this area found that Ghanaian taxi drivers accept lower prices from co-partisans and

demand higher prices from counter-partisans. Specifically, non-coethnic counter-partisans

pay 16% more and non-coethnic co-partisans 6% more in taxi fares than coethnic co-

partisans, suggesting an interaction between both ethnicity and partisanship. McConnell

et al. (2018) conducted a field experiment in the U.S. in which people were provided the op-

portunity to buy a heavily discounted gift card. Some buyers were assigned to conditions in

which they learned that the seller was either a co-partisan or counter-partisan. They found

no evidence of out-group animus; the purchasing rate remained stable across same party

and opposite party sellers. However, interacting with a co-partisan seller nearly doubled

the purchasing price of the gift card. The effects were even larger among strong partisans.

Panagopoulos et al. (2016), on the other hand, find evidence of out-group animus: 15%-

20% of participants in their study were less willing to accept a gift card from a company

that gives PAC donations to the opposing party. While Panagopoulos et al. (2016) observe

larger effect sizes than McConnell et al. (2018), that could be because their study took place

within the less-natural context of a survey experiment. Indeed, in Panagopoulos et al.’s

(2016) replication study done in the field, the effect sizes fell to about 5 percentage points.

In addition to product markets, partisanship can distort labor markets. Using an audit

design, Gift and Gift (2015) mailed out resumes signaling job applicants’ partisan affiliation

in a heavily Democratic area and a heavily Republican area. They find that in the Democratic

county, Democratic resumes were 2.4 percentage points more likely to receive a callback

than Republican resumes; the corresponding partisan preference for Republican resumes in

the Republican county was 5.6 percentage points. Whereas Gift and Gift (2015) examine

employer preferences, McConnell et al. (2018) examine the other side of the labor market and

study how partisanship affects employee behavior. The researchers hired workers to complete

an online editing task and subtly signalled the partisan identification of the employer. Unlike

Gift and Gift (2015), they mainly find evidence of in-group affinity as opposed to out-group

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prejudice. The only significant differences occurred between the co-partisan condition and

the control group. People exhibited a willingness to accept lower compensation (by 6.5%)

from a partisan congruent employer. At the same time, they performed lower-quality work

and exhibited less effort. Although the mechanism for this performance deficit is unclear,

one possibility is that they perceive the employer to be of higher quality and therefore less

likely to make copy-editing mistakes.

In addition to affecting economic decisions, partisanship colors how people perceive the

state of the economy. A seminal finding in political behavior research is that people tend to

believe that economic outcomes (e.g., GDP growth, unemployment rate) are more favorable

(unfavorable) when their party is in (out of) the White House (Bartels, 2002). These percep-

tual biases seem most pronounced when the actual state of the economy is ambiguous (Healy

and Malhotra, 2013). These findings have recently been challenged on the grounds that sur-

vey responses are expressive cheap talk (Bullock et al., 2015; Prior, Sood, and Khanna,

2015). The partisan gap in economic perceptions narrows—but does not disappear—when

survey respondents are financially incentivized to provide accurate answers about the state

of the economy. Of more course, one concern with these findings is that voting, like the

typical survey response, is an expressive act, not an incentivized one (see also Berinsky,

2018). Moreover, the correlation between vote choice and non-incentivized economic beliefs

outstrips the correlation between vote choice and incentivized beliefs, suggesting that paying

survey particioants to be honest only results in an expensive version of cheap talk.

Given the concerns over the motives of survey respondents, scholars have used research

designs less subject to partisan cheerleading. For instance, Gerber and Huber (2010) find

that when party control of Congress switches, consumer behavior changes, and changes

along party lines, in anticipation of changes in the economy. After the Democrats took

over Congress in 2006, strong Democrats showed a 12.8% increase in holiday spending and

a 30.5% increase in vacation spending relative to strong Republicans. In an earlier study,

Gerber and Huber (2009) used data from county tax receipts to estimate that a county that

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moves from 50% Democratic to 65% Democratic undergoes an increase in consumption .9%

higher following a Democratic presidential victory compared with a Republican presidential

victory. However, these empirical results have recently been challenged (McGrath, 2017),

and the relationship between partisanship and economic perceptions remains an important

area of scholarly inquiry.

Partisanship may spill over into other professional decisions as well. For example, Wintoki

and Xi (2017) find that mutual fund managers are more likely to invest in companies managed

by co-partisans. Although this behavior may be unconscious or due to selection on some

other dimension, it seems to conflict with the fiduciary duties of managers as partisan bias

does not improve fund performance and actually increases volatility. In medicine, Hersh and

Goldenberg (2016) find that Republican and Democratic physicians give different advice to

patients for politicized health issues such as abortion, but not on apolitical health topics. On

the patient side, Lerman, Sadin, and Trachtman (2017) leverage longitudinal data and find

that Republicans were less likely than Democrats to enroll in health insurance exchanges set

up by the Affordable Care Act, and Krupenkin (2016) shows that parents are more likely to

vaccinate their children when their party’s president is in the White House.

While we have focused here on the non-political consequences of affective polarization

and partisan animus, there is also the question of the political consequences of this phe-

nomenon. Interestingly, little has been written on this topic, as most studies have focused

on the more surprising apolitical ramifications discussed above. There are two important

counter-examples, however. First, there is evidence that affective polarization and out-party

animus fuels political activity: individuals’ dislike for the opposing party encourages them

to participate more in politics (Iyengar and Krupenkin, 2018). Second, another strand of

research by Hetherington and Rudolph (2015) shows that affective polarization undermines

trust on the part of the party that is out of power, and hence makes governing more complex.

This is only the beginning of research into the consequences of affective polarization.

More research is needed to understand how these factors play out in a variety of different

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political contexts. For instance, do increases in affective polarization among the mass public

increase partisan discord among elites? More generally, does affective polarization threaten

to undermine the very mechanisms of electoral accountability through which elected officials

can be punished for misdeeds? Were Republicans in Alabama so hostile toward Democratic

Senate candidate Doug Jones that almost all of them voted for a candidate accused of

multiple sexual indiscretions? More research is needed to fully flesh out these behaviors.

Decreasing Affective Polarization

What, if anything, can be done to ameliorate affective polarization? While efforts here are at

best nascent, several approaches have shown promise. All of them work to reduce the biases

generated by partisanship’s division of the world into an in-group and an out-group. Hence,

some work has focused on making partisan identities less salient or making other identities

more salient.

First, scholars have shown that correcting misperceptions about party supporters reduces

animus toward the other side (Ahler and Sood, Forthcoming). The modal member of both

parties is a middle-aged, white, non-evangelical Christian, but this is not the image most

people carry around in their heads when they think about “Democrats” and “Republicans.”

Instead, most people think in terms of partisan stereotypes: Democrats are urban minorities

and young people, Republicans are older, wealthy, or evangelical Christians. Consequently,

when the typical American is asked about the composition of the parties, she tends to dra-

matically over-report the prevalence of partisan-stereotypical groups. While only about 11

percent of Democrats belong to a labor union, in a large national survey, the average Amer-

ican thought that 39 percent of Democrats were union members (44 percent of Republicans

had this perception along with 37 percent of Democrats). Likewise, while only 2.2 percent of

Republicans earn more than $250,000 per year, the average citizen thought that 38 percent of

Republicans earned that much. Looking across a range of party-stereotypical groups, Ahler

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and Sood (Forthcoming) find that respondents over-estimate the prevalence of these groups

by 342 percent (5-6). These biases matter because people typically hold negative views to-

ward the other party’s stereotypical groups (see also Homola et al., 2016; Levendusky and

Malhotra, 2016b).4

If misperceptions about party composition increase partisan animus, possibly correcting

them could reduce affective polarization. Happily, this is exactly what scholars find. When

Ahler and Sood (Forthcoming) correct respondents misperceptions, respondents think the

other party is less extreme, and affective polarization decreases (i.e., they like the other

party more). In essence, people dislike the other party in part because they (inaccurately)

perceive it to be quite different from themselves and full of disliked groups. When this error

is corrected, and they realized the partisan out-group is more similar to them than they had

realized, animus lessens.5

A second approach tries to shift the salience of respondents’ partisan identities. Nor-

mally, when Democrats and Republicans think about one another, they perceive them as

members of a disliked partisan out-group. But they are also members of a common group:

they are all Americans. If Democrats and Republicans see one another as Americans, rather

than partisans, they move from out-group members to in-group ones, and hence group-based

partisan animus should fade. Using a set of survey experiments, as well as a natural exper-

iment stemming from the July Fourth holiday, Levendusky (2018) shows that emphasizing

American identity reduces animus toward the other party. For example, in his experimental

results, treated subjects (who had their American identity primed) were 25% less likely to

rate the other party at 0 degrees on a feeling thermometer scale, and 35% more likely to rate

4While Ahler and Sood (Forthcoming) do a commendable job of reviewing the consequences of suchmisperceptions, they have less to say about the causes of such erroneous beliefs. They offer some initialevidence that those who consume more political news hold more biased beliefs (see their Figure 2), suggestinga role for media coverage of the parties. More careful documentation of the sources of these stereotypes willbe an important step for future research.

5Similarly, Ahler (2014) shows that when people are explicitly told how moderate the average Americanis, respondents also become more moderate—correcting misperceptions can also mitigate ideological polar-ization as well. However, Levendusky and Malhotra (2016a) reach different conclusions using a differentoperationalization of the treatment.

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the other party at 50 degrees or higher; there are similar effects for ratings of various traits

as well (see similar results by Carlin and Love (2018) on the capture of Osama bin Laden).

By showing what unites Democrats and Republicans, rather than emphasizing what divides

and differentiates them, partisan animus subsides.

More generally, the evidence suggests that making partisanship and politics less salient—

and emphasizing other factors—can potentially change behavior as well. For example, Ler-

man, Sadin, and Trachtman (2017) partnered with an outside organization (Enroll America)

to help uninsured individuals obtain health insurance through the federal marketplace. In-

dividuals who went to Enroll America’s website were directed either to the government-run

website (healthcare.gov) or to a private website (HealthSherpa.com). While the website

has no effect on the behavior of Democrats or Independents, it has an enormous effect on

Republicans: Republicans assigned to the private website are 20 percentage points more

likely to enroll in an insurance plan than Republicans assigned to the government website

(see their Figure 4 and the discussion on p. 764). Likely because of President Obama’s

association with the health insurance exchanges, partisan considerations shape Republicans

behavior here. But when they are shown a private website—which obscures the government’s

role—they become more willing to enroll. In an era of affective polarization, downplaying

politics can help to mitigate partisan divisions.

Both of these approaches represent important contributions to the literature, and high-

light important pathways to reducing partisan discord in the mass public. But there are two

important limitations to note. First, while both types of efforts appear to be effective, we

should not expect it to be easy to reduce partisan animus, even in the survey context, where

behavior tends to be quite malleable. While some strategies will work, many sensible strate-

gies will fail. For example, Levendusky (2017) uses a population-based survey experiment

to show that priming partisan ambivalence and using self-affirmation techniques—both of

which have been shown to reduce similar biases in other contexts—fail to reduce partisan

animus. It may be that in the contemporary political era, when partisanship is chronically

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accessible, only quite strong primes are able to reduce affective polarization.

Further, it is unclear to what extent treatments that work in a survey experiment (or

other controlled settings) work in the messy reality of real-world politics. Even showing

that it is possible to reduce affective polarization and discord within the confines of a survey

experiment is an important contribution, but another important step for future research will

be to demonstrate that such effects can be generalized.

One potentially promising strand of research is to build off the insights of inter-group

contact theory (Pettigrew and Tropp, 2011) and examine whether constructive engagement

between Democrats and Republicans could potentially reduce partisan animus. This is also

related to a long tradition of work showing that diverse social networks—which expose

individuals to different political points of view—foster tolerance for opposing viewpoints,

which should also ameliorate affective polarization (Mutz, 2002). For example, several groups

have fostered small-scale discussions between ordinary Democrats and Republicans to try

and bridge the gap between the parties (Nelson, 2015). But there have been no systematic

evaluations of these efforts, and it seems questionable whether such efforts are scalable.

Open Questions and Concluding Thoughts

In this closing section we identify future research agendas and offer some thoughts on the

political significance of intensified partisan affect in the current era.

First, there has been little to no research identifying the mechanisms underlying affective

polarization. On the one hand, distaste for opposing partisans could be couched in raw,

reflexive emotion. This could result in extreme political responses based on blind hatred.

However, psychologists have long suggested that affect has informational content, so height-

ened affective polarization may also lead to more considered responses to both in and out

groups. For instance, the aversion to engage in economic transactions with opposing parti-

sans may stem not from a visceral emotional response, but because opponents are seen as

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untrustworthy. This is akin to the distinction in the economics literature between animus

and statistical discrimination. Of course, existing research has noted that people’s stereo-

types of opposing partisans traits are inaccurate (both in terms of means and variances), so

distinguishing between these mechanisms seems important.

Second, the literature has yet to specify the conditions under which partisans are moti-

vated by either in-group favoritism or out-group animosity. Although social psychologists

studying group conflict have generally concluded that in-group affection is the dominant

force, the domain of politics might be distinctive. There is ample evidence that political

judgment is subject to a negativity bias (Soroka, 2014), implying that party polarization is

driven by out-group hostility. However, there is also evidence that in some situations par-

tisan bias is prompted more by in-group love (Lelkes and Westwood, 2017). One plausible

hypothesis is that the precise mix of in- and out-group sentiment will depend on individuals

prior information and how they update beliefs based on exposure to new information. For

instance, McConnell et al. (2018) found that consumers exhibited in-group favoritism toward

co-partisan sellers but not out-group animus toward opposite-party sellers. Perhaps this is

because their experimental participants had no prior relationship with the seller. On the

other hand, when people respond to a more well-known brand with which they have had a

previous relationship, they may be more likely to exhibit out-group animus in response to

partisan information and update negatively (as in Panagopoulos et al. (2016)). It is also

possible that the role of in groups and out groups in decision making is task dependent.

Social psychologists have suggested that contextual effects such as competition and threat

alter the degree to which people punish opponents or reward team members (Brewer, 1999).

Future research can more explicitly incorporate updating into experimental designs intended

to identify the relative contributions of in- and out-group sentiment to affective polarization.

As a third agenda item, we encourage researchers to explore the role of sorting as a

potential mediator of affective polarization. To the extent the alignment of ideology and

partisanship exacerbates polarization, sorted partisans should elicit a stronger outpouring

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of either in-group favoritism or out-group animus. Yet we know of no work to date assesses

differences in partisans affect toward sorted and unsupported co-partisans or opponents.

Relatedly, scholars should examine the relative influence of social identities versus ideo-

logical sorting on affective polarization. Recent work indicates that while ideological polar-

ization, sorting, and affective polarization are correlated (Rogowski and Sutherland, 2016;

Bougher, 2017; Webster and Abramowitz, 2017), the relationship is rather weak, with sort-

ing accounting for only about 5 percent of the variance in affective polarization (Lelkes,

Forthcoming; Mason, 2018a). Furthermore, over the past 40 years, affective polarization in-

creased by about the same amount among those who held the most ideologically consistent

issue positions as those who held the least ideologically consistent issue positions (Lelkes,

Forthcoming). Further complicating any claim that affective polarization is a byproduct of

ideological sorting is the possibility that affective polarization may, in turn, increase sorting.

The most affectively polarized may be more likely to toe the party line and adopt party

policy positions.

Fourth, no research that we are aware of has identified ways in which affective polarization

drives both elite and mass ideological polarization. In terms of the former, we suspect that

affective polarization increases support for extremist politicians, or, at least, blinds partisans

to the ideological extremity of candidates from their party. In terms of the latter, we suspect

that affective polarization increases partisans’ willingness to conform to their party’s policy

positions. Hence, affective polarization may yield extreme politicians, who then send policy

cues to their base, exacerbating mass ideological polarization.

Finally, there has been little effort to draw out the connections between the American

politics literature on affective polarization and similar literatures in comparative politics

(though see Westwood et al. (2017) and Carlin and Love (2018)). Comparativists have

long recognized the importance of group identity to political behavior and attitudes, even

if they have not used the language of social identity theory or affective polarization. A

wide variety of findings in the literatures on ethnicity and distributive politics, as well as

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on political violence, provide important theoretical and empirical insights for the study of

affective polarization. While we lack the space to review this literature here, more work is

needed to build bridges between Americanists and comparativists interested in these topics.

In conclusion, we note that increasing affective polarization can have grave ramifications,

especially during times of political turmoil. There is a broad similarity between the current

state of the Trump administration and the Watergate years; and yet, heightened polarization

has altered the political context in important ways. The Watergate scandal was brought to

light by investigative news reports that, over time, became widely accepted as credible and

eventually resulted in significant erosion of President Nixons approval among both Democrats

and Republicans alike (Lebo and Cassino, 2007). In contrast, the current pervasive drip of

scandal touching on the Trump administration has done little to weaken President Trump’s

popularity among Republicans who accuse the press and investigative bodies of partisan

bias (although see, Montagnes, Peskowitz, and McCrain, 2018). Partisanship appears to

now compromise the norms and standards we apply to our elected representatives, and even

leads partisans to call into question the legitimacy of election results, both of which threatens

the very foundations of representative democracy.

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